Abstract
Glycosylation is the most common form of post-translational modification of proteins, critically affecting their structure and function. Using liquid chromatography and mass spectrometry for high-resolution site-specific quantification of glycopeptides coupled with high-throughput artificial intelligence-powered data processing, we analyzed differential protein glycoisoform distributions of 597 abundant serum glycopeptides and nonglycosylated peptides in 50 individuals who had been seriously ill with COVID-19 and in 22 individuals who had recovered after an asymptomatic course of COVID-19. As additional comparison reference phenotypes, we included 12 individuals with a history of infection with a common cold coronavirus, 16 patients with bacterial sepsis, and 15 healthy subjects without history of coronavirus exposure. We found statistically significant differences, at FDR < 0.05, for normalized abundances of 374 of the 597 peptides and glycopeptides interrogated between symptomatic and asymptomatic COVID-19 patients. Similar statistically significant differences were seen when comparing symptomatic COVID-19 patients to healthy controls (350 differentially abundant peptides and glycopeptides) and common cold coronavirus seropositive subjects (353 differentially abundant peptides and glycopeptides). Among healthy controls and sepsis patients, 326 peptides and glycopeptides were found to be differentially abundant, of which 277 overlapped with biomarkers that showed differential expression between symptomatic COVID-19 cases and healthy controls. Among symptomatic COVID-19 cases and sepsis patients, 101 glycopeptide and peptide biomarkers were found to be statistically significantly abundant. Using both supervised and unsupervised machine learning techniques, we found specific glycoprotein profiles to be strongly predictive of symptomatic COVID-19 infection. LASSO-regularized multivariable logistic regression and K-means clustering yielded accuracies of 100% in an independent test set and of 96% overall, respectively. Our findings are consistent with the interpretation that a majority of glycoprotein modifications observed which are shared among symptomatic COVID-19 and sepsis patients likely represent a generic consequence of a severe systemic immune and inflammatory state. However, there are glycoisoform changes that are specific and particular to severe COVID-19 infection. These may be representative of either COVID-19-specific consequences or susceptibility to or predisposition for a severe course of the disease. Our findings support the potential value of glycoproteomic biomarkers in the biomedical understanding and, potentially, the clinical management of serious acute infectious conditions.
Highlights
Coronavirus disease 2019 (COVID-19) is a highly contagious infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)
COVID-19, 22 serum samples from individuals without a history of symptomatic COVID-19 illness who were found to be seropositive for SARS-CoV-2-antibodies when they presented as blood bank donors, 16 plasma samples from patients who had presented with bacterial sepsis (8 mild, 8 severe), 12 plasma samples from patients who were positive by polymerase chain-reaction (PCR) for a common cold-presenting coronavirus, and 15 serum samples of healthy, coronavirus seronegative controls
Samples from patients with symptomatic COVID-19 demonstrated glycoprotein profiles that are clearly different from those found in individuals who had experienced an asymptomatic or comparatively mild course of the disease
Summary
Coronavirus disease 2019 (COVID-19) is a highly contagious infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The illness, characterized in severe cases by respiratory distress syndrome, was initially recognized in December 2019 in the city of Wuhan, People’s Republic of China, spreading subsequently across the country and, very quickly, across the world as a pandemic of unprecedented impact and duration. The majority of COVID-19 cases generally only suffer mild symptoms or remain fully asymptomatic, the pandemic has caused more than 5.1 million deaths worldwide, with many more having experienced a serious and life-threatening illness. Cardiovascular diseases, hypertension, and chronic respiratory diseases, as well as advanced age, male sex, sociocultural factors, and ethnicity, have all been found to be associated with a heightened risk of severe disease or death, as have certain germline genetic variants. No one or combination of these factors fully explains the heterogeneity in outcomes observed with the disease
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